-------------------------------------------------------------------------------------------------------------------------------------------
       log:  C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\table1b.log
  log type:  text
 opened on:   3 May 2006, 22:51:00

. ****************************************************
. * 11 - MidGround to Democracy - Education Exchange
. ****************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-dem-stset.dta", clear

. *use "mid-to-dem-stset.dta"
. notes

_dta:
  1.  Data compiled by Carol Atkinson.
  2.  When using cite: Atkinson, Carol. 2006. Constructivist Implications of Material Power: Military Engagement and the Socialization of
      States 1972-2000. International Studies Quarterly. September.

. describe

Contains data from C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-dem-stset.dta
  obs:         1,256                          
 vars:            27                          3 May 2006 21:48
 size:       155,744 (98.5% of memory free)   (_dta has notes)
-------------------------------------------------------------------------------
              storage  display     value
variable name   type   format      label      variable label
-------------------------------------------------------------------------------
ccode           float  %9.0g                  
country         str24  %24s                   
abbrev          str8   %8s                    
year            float  %9.0g                  
polity2         float  %9.0g                  Polity2+10, inconsistencies
                                                removed from conversion of
                                                -66, -77, -88
IMETyesno       float  %9.0g                  IMET indicator,
                                                1=attendance/funding that year,
                                                0=not
Ally            float  %9.0g                  Alliance membership with the
                                                US, 1=yes, 0=no
USMil_normfor~l float  %9.0g                  US Military Overseas normalized
                                                by size of foreign military
USmil_sales_n~m float  %9.0g                  US military sales/GDP-current
USmilasst_norm  float  %9.0g                  US military
                                                assistance/GDP-current
USmilact_yesno  float  %9.0g                  1=threat, display, use of
                                                force, war; 0= no militarized
                                                action by US
soviet_foreig~t float  %9.0g                  Countries receiving foreign
                                                assistance from the USSR during
                                                the Cold War
USeconaid_norm  float  %9.0g                  US economic aid/GDP-current
newc            float  %9.0g                  New country in or after 1945
britcol         float  %9.0g                  Former British colony
open_i          float  %9.0g                  Trade openness indicator
GDP_rescaled    float  %9.0g                  GDP_PPP_per_capita / 1000
Ethnic_gp       float  %9.0g                  Percentage of the population
                                                that is of the country's
                                                largest ethnic group
muslim_majori~o float  %9.0g                  Muslim majority indicator,
                                                Muslims are at least 50%=1, 0
                                                otherwise
christian_maj~o float  %9.0g                  Christian majority indicator,
                                                Christians are at least 50%=1,
                                                0 otherwise
LatAm           float  %9.0g                  1=country in Central or South
                                                America, 0=not
mildictator     float  %9.0g                  Military dictatorship
                                                indicator, 1=military dictator,
                                                0=otherwise
ccode1          float  %9.0g                  
_st             byte   %8.0g                  
_d              byte   %8.0g                  
_t              byte   %10.0g                 
_t0             byte   %10.0g                 
-------------------------------------------------------------------------------
Sorted by:  ccode  year

. gen britcolxtime = britcol*_t

. gen IMETyesnoxtime=IMETyesno*_t

. #delimit ;
delimiter now ;
. stcox 
> IMETyesno
> USmilact_yesno
> soviet_foreign_asst
> USeconaid_norm 
> newc
> britcol
> open_i 
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno 
> IMETyesnoxtime
> britcolxtime,
> bases(mgtodem_surv) basehc(mgtodem_hazard) basechazard(mgtodem_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d1 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -163.55618
Iteration 1:   log pseudolikelihood = -145.82449
Iteration 2:   log pseudolikelihood = -144.21358
Iteration 3:   log pseudolikelihood = -143.66385
Iteration 4:   log pseudolikelihood = -143.31118
Iteration 5:   log pseudolikelihood = -143.10974
Iteration 6:   log pseudolikelihood = -143.05765
Iteration 7:   log pseudolikelihood = -143.05448
Iteration 8:   log pseudolikelihood = -143.05447
Refining estimates:
Iteration 0:   log pseudolikelihood = -143.05447

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           41
Time at risk         =         1180
                                                   Wald chi2(13)   =     26.08
Log pseudolikelihood =   -143.05447                Prob > chi2     =    0.0166

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   IMETyesno |   2.009918   .7852742     2.56   0.010     .4708087    3.549027
USmilact_y~o |   .3662501   1.248031     0.29   0.769    -2.079846    2.812346
soviet_for~t |   .5491837    .441105     1.25   0.213    -.3153663    1.413734
USeconaid_~m |   .3818027   8.555759     0.04   0.964    -16.38718    17.15078
        newc |  -.1896326   .4130675    -0.46   0.646      -.99923    .6199647
     britcol |   1.608851   1.037451     1.55   0.121    -.4245155    3.642218
      open_i |  -.0047498   .0048605    -0.98   0.328    -.0142762    .0047767
GDP_rescaled |   .1069999   .0527862     2.03   0.043     .0035407     .210459
   Ethnic_gp |   1.280372   .7620607     1.68   0.093    -.2132397    2.773983
muslim_maj~o |  -.1007725   .5309153    -0.19   0.849    -1.141347    .9398023
christian_~o |    .294591   .3743112     0.79   0.431    -.4390453    1.028227
IMETyesnox~e |  -.1449592   .0683329    -2.12   0.034    -.2788893   -.0110291
britcolxtime |  -.6398599   .3560612    -1.80   0.072    -1.337727    .0580072
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      IMETyesno   |     -0.03444         0.09        1         0.7678
      USmilact_y~o|      0.06029         0.31        1         0.5770
      soviet_for~t|      0.01082         0.01        1         0.9336
      USeconaid_~m|      0.10522         0.53        1         0.4652
      newc        |      0.20526         3.02        1         0.0821
      britcol     |     -0.00095         0.00        1         0.9946
      open_i      |      0.02549         0.04        1         0.8445
      GDP_rescaled|     -0.15869         0.78        1         0.3771
      Ethnic_gp   |     -0.10197         0.92        1         0.3373
      muslim_maj~o|     -0.21747         3.20        1         0.0736
      christian_~o|     -0.12169         0.41        1         0.5231
      IMETyesnox~e|      0.03241         0.07        1         0.7944
      britcolxtime|     -0.04311         0.10        1         0.7554
      ------------+---------------------------------------------------
      global test |                      9.54       13         0.7309
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. *********************************************
. * 12 - MidGround to Democracy - Ally With US 
. *********************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-dem-stset.dta", clear

. *use "mid-to-dem-stset.dta"
. gen britcolxtime = britcol*_t

. #delimit ;
delimiter now ;
. stcox 
> Ally
> USmilact_yesno
> soviet_foreign_asst
> USeconaid_norm 
> newc
> britcol
> open_i 
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno
> britcolxtime,
> bases(mgtodem_surv) basehc(mgtodem_hazard) basechazard(mgtodem_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d1 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -163.55618
Iteration 1:   log pseudolikelihood =   -149.292
Iteration 2:   log pseudolikelihood = -147.58478
Iteration 3:   log pseudolikelihood = -147.04971
Iteration 4:   log pseudolikelihood = -146.68197
Iteration 5:   log pseudolikelihood = -146.45924
Iteration 6:   log pseudolikelihood = -146.40237
Iteration 7:   log pseudolikelihood = -146.39911
Iteration 8:   log pseudolikelihood =  -146.3991
Refining estimates:
Iteration 0:   log pseudolikelihood =  -146.3991

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           41
Time at risk         =         1180
                                                   Wald chi2(12)   =     24.66
Log pseudolikelihood =    -146.3991                Prob > chi2     =    0.0165

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        Ally |   .6542369   .4779127     1.37   0.171    -.2824548    1.590929
USmilact_y~o |  -.3268681   1.321021    -0.25   0.805    -2.916022    2.262285
soviet_for~t |   .3603531   .4437866     0.81   0.417    -.5094527    1.230159
USeconaid_~m |    2.64964   9.187293     0.29   0.773    -15.35712     20.6564
        newc |   -.161137   .4903607    -0.33   0.742    -1.122226    .7999523
     britcol |   1.934937   1.142841     1.69   0.090    -.3049905    4.174864
      open_i |  -.0050922   .0050188    -1.01   0.310    -.0149288    .0047444
GDP_rescaled |   .1271395   .0477042     2.67   0.008      .033641     .220638
   Ethnic_gp |   .7583695   .7335881     1.03   0.301    -.6794367    2.196176
muslim_maj~o |   .2569644   .5771441     0.45   0.656    -.8742171    1.388146
christian_~o |   .1550196   .4325423     0.36   0.720    -.6927476    1.002787
britcolxtime |  -.6923782    .414028    -1.67   0.094    -1.503858    .1191017
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      Ally        |     -0.07178         0.76        1         0.3842
      USmilact_y~o|      0.10402         1.13        1         0.2874
      soviet_for~t|      0.01724         0.02        1         0.8817
      USeconaid_~m|      0.12164         0.88        1         0.3493
      newc        |      0.10324         1.19        1         0.2753
      britcol     |     -0.03402         0.08        1         0.7736
      open_i      |      0.05976         0.20        1         0.6563
      GDP_rescaled|     -0.11821         0.51        1         0.4755
      Ethnic_gp   |     -0.13117         1.93        1         0.1650
      muslim_maj~o|     -0.16363         3.20        1         0.0734
      christian_~o|     -0.14872         0.85        1         0.3562
      britcolxtime|     -0.02900         0.09        1         0.7682
      ------------+---------------------------------------------------
      global test |                     10.92       12         0.5357
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. ***********************************************************
. * 13 - MidGround to Democracy - US Military Troop Presence
. ***********************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-dem-stset.dta", clear

. *use "mid-to-dem-stset.dta"
. gen britcolxtime = britcol*_t

. #delimit ;
delimiter now ;
. stcox 
> USMil_normforeignMil
> USmilact_yesno
> soviet_foreign_asst
> USeconaid_norm 
> newc
> britcol
> open_i 
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno
> britcolxtime,
> bases(mgtodem_surv) basehc(mgtodem_hazard) basechazard(mgtodem_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d1 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -163.55618
Iteration 1:   log pseudolikelihood = -150.20121
Iteration 2:   log pseudolikelihood = -148.81423
Iteration 3:   log pseudolikelihood = -148.20156
Iteration 4:   log pseudolikelihood = -147.78606
Iteration 5:   log pseudolikelihood = -147.53513
Iteration 6:   log pseudolikelihood = -147.46421
Iteration 7:   log pseudolikelihood =  -147.4592
Iteration 8:   log pseudolikelihood = -147.45917
Refining estimates:
Iteration 0:   log pseudolikelihood = -147.45917

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           41
Time at risk         =         1180
                                                   Wald chi2(12)   =     21.29
Log pseudolikelihood =   -147.45917                Prob > chi2     =    0.0463

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
USMil_norm~l |  -1.066436   1.317015    -0.81   0.418    -3.647738    1.514867
USmilact_y~o |  -.2847279   1.342573    -0.21   0.832    -2.916123    2.346667
soviet_for~t |   .2977451   .4622007     0.64   0.519    -.6081516    1.203642
USeconaid_~m |   1.287572   8.528685     0.15   0.880    -15.42834    18.00349
        newc |  -.3355979   .4259988    -0.79   0.431     -1.17054    .4993444
     britcol |   1.968735   1.144612     1.72   0.085    -.2746637    4.212134
      open_i |  -.0058629   .0049822    -1.18   0.239    -.0156279     .003902
GDP_rescaled |   .1152272   .0468386     2.46   0.014     .0234253    .2070292
   Ethnic_gp |   1.096445   .6438972     1.70   0.089      -.16557    2.358461
muslim_maj~o |   .0656788   .5455782     0.12   0.904    -1.003635    1.134992
christian_~o |   .2900656   .4020061     0.72   0.471    -.4978518    1.077983
britcolxtime |  -.7162619   .4029655    -1.78   0.075     -1.50606    .0735359
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      USMil_norm~l|     -0.02403         0.01        1         0.9085
      USmilact_y~o|      0.13074         1.87        1         0.1712
      soviet_for~t|     -0.00076         0.00        1         0.9944
      USeconaid_~m|      0.17027         1.33        1         0.2483
      newc        |      0.20935         3.52        1         0.0606
      britcol     |      0.00696         0.00        1         0.9609
      open_i      |      0.07587         0.30        1         0.5829
      GDP_rescaled|     -0.00506         0.00        1         0.9769
      Ethnic_gp   |     -0.17086         2.06        1         0.1507
      muslim_maj~o|     -0.23600         4.93        1         0.0263
      christian_~o|     -0.10191         0.36        1         0.5460
      britcolxtime|     -0.04888         0.15        1         0.7027
      ------------+---------------------------------------------------
      global test |                     12.45       12         0.4106
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. **************************************************
. * 14 - MidGround to Democracy - US Military Sales
. **************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-dem-stset.dta", clear

. *use "mid-to-dem-stset.dta"
. gen britcolxtime = britcol*_t

. #delimit ;
delimiter now ;
. stcox 
> USmil_sales_norm
> USmilact_yesno
> soviet_foreign_asst
> USeconaid_norm 
> newc
> britcol
> open_i 
> GDP_rescaled
> Ethnic_gp
> muslim_majority_yesno 
> christian_majority_yesno
> britcolxtime,
> bases(mgtodem_surv) basehc(mgtodem_hazard) basechazard(mgtodem_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d1 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -163.55618
Iteration 1:   log pseudolikelihood = -150.23519
Iteration 2:   log pseudolikelihood = -148.75064
Iteration 3:   log pseudolikelihood = -148.07488
Iteration 4:   log pseudolikelihood = -147.61074
Iteration 5:   log pseudolikelihood = -147.33533
Iteration 6:   log pseudolikelihood =  -147.2591
Iteration 7:   log pseudolikelihood = -147.25349
Iteration 8:   log pseudolikelihood = -147.25345
Refining estimates:
Iteration 0:   log pseudolikelihood = -147.25345

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           41
Time at risk         =         1180
                                                   Wald chi2(12)   =     20.68
Log pseudolikelihood =   -147.25345                Prob > chi2     =    0.0553

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
USmil_sale~m |   64.30925   56.26514     1.14   0.253    -45.96839    174.5869
USmilact_y~o |  -.2891536   1.334977    -0.22   0.829    -2.905661    2.327354
soviet_for~t |   .3080633   .4556184     0.68   0.499    -.5849324    1.201059
USeconaid_~m |  -3.198034   12.01329    -0.27   0.790    -26.74365    20.34758
        newc |  -.2792863   .4311535    -0.65   0.517    -1.124332    .5657591
     britcol |   1.990639   1.120384     1.78   0.076    -.2052727     4.18655
      open_i |  -.0063899   .0050651    -1.26   0.207    -.0163174    .0035375
GDP_rescaled |   .1142614   .0474648     2.41   0.016     .0212321    .2072907
   Ethnic_gp |   .9779466   .6455268     1.51   0.130    -.2872628    2.243156
muslim_maj~o |   .0959398   .5356789     0.18   0.858    -.9539715    1.145851
christian_~o |   .3204012   .3989549     0.80   0.422    -.4615361    1.102338
britcolxtime |  -.7428265   .3891324    -1.91   0.056    -1.505512     .019859
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      USmil_sale~m|     -0.12302         0.43        1         0.5104
      USmilact_y~o|      0.12508         1.71        1         0.1908
      soviet_for~t|      0.00731         0.00        1         0.9487
      USeconaid_~m|      0.14858         1.18        1         0.2778
      newc        |      0.19295         3.07        1         0.0800
      britcol     |     -0.01895         0.02        1         0.8951
      open_i      |      0.08557         0.38        1         0.5354
      GDP_rescaled|      0.00363         0.00        1         0.9831
      Ethnic_gp   |     -0.17792         2.15        1         0.1422
      muslim_maj~o|     -0.24400         4.87        1         0.0273
      christian_~o|     -0.12145         0.51        1         0.4747
      britcolxtime|     -0.02460         0.03        1         0.8580
      ------------+---------------------------------------------------
      global test |                     12.24       12         0.4269
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. *******************************************************
. * 15 - MidGround to Democracy - US Military Assistance
. *******************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-dem-stset.dta", clear

. *use "mid-to-dem-stset.dta"
. gen britcolxtime = britcol*_t

. #delimit ;
delimiter now ;
. stcox 
> USmilasst_norm
> USmilact_yesno
> soviet_foreign_asst
> USeconaid_norm 
> newc
> britcol
> open_i 
> GDP_rescaled
> Ethnic_gp
> muslim_majority_yesno 
> christian_majority_yesno
> britcolxtime,
> bases(mgtodem_surv) basehc(mgtodem_hazard) basechazard(mgtodem_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d1 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -163.55618
Iteration 1:   log pseudolikelihood = -150.34247
Iteration 2:   log pseudolikelihood = -148.94018
Iteration 3:   log pseudolikelihood = -148.32575
Iteration 4:   log pseudolikelihood = -147.90779
Iteration 5:   log pseudolikelihood = -147.65304
Iteration 6:   log pseudolikelihood = -147.57936
Iteration 7:   log pseudolikelihood = -147.57394
Iteration 8:   log pseudolikelihood = -147.57391
Refining estimates:
Iteration 0:   log pseudolikelihood = -147.57391

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           41
Time at risk         =         1180
                                                   Wald chi2(12)   =     20.90
Log pseudolikelihood =   -147.57391                Prob > chi2     =    0.0518

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
USmilasst_~m |   6.562338   25.45603     0.26   0.797    -43.33057    56.45525
USmilact_y~o |  -.3002632   1.329734    -0.23   0.821    -2.906494    2.305967
soviet_for~t |   .3089469   .4553569     0.68   0.497    -.5835362     1.20143
USeconaid_~m |   .7066293    9.78878     0.07   0.942    -18.47903    19.89229
        newc |  -.3110786   .4210262    -0.74   0.460    -1.136275    .5141176
     britcol |    1.97044   1.151515     1.71   0.087     -.286487    4.227367
      open_i |  -.0062004   .0050043    -1.24   0.215    -.0160086    .0036078
GDP_rescaled |   .1162014   .0468817     2.48   0.013      .024315    .2080879
   Ethnic_gp |   1.055737   .6372588     1.66   0.098    -.1932676    2.304741
muslim_maj~o |   .0753581   .5395059     0.14   0.889     -.982054     1.13277
christian_~o |   .2867549   .4039829     0.71   0.478    -.5050371    1.078547
britcolxtime |  -.7228043   .4133622    -1.75   0.080    -1.532979    .0873706
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      USmilasst_~m|     -0.18333         0.67        1         0.4129
      USmilact_y~o|      0.12833         1.76        1         0.1851
      soviet_for~t|      0.00572         0.00        1         0.9597
      USeconaid_~m|      0.19016         1.67        1         0.1962
      newc        |      0.20008         3.08        1         0.0793
      britcol     |     -0.00411         0.00        1         0.9772
      open_i      |      0.08791         0.38        1         0.5355
      GDP_rescaled|     -0.00137         0.00        1         0.9938
      Ethnic_gp   |     -0.17099         1.99        1         0.1583
      muslim_maj~o|     -0.23594         4.71        1         0.0300
      christian_~o|     -0.10230         0.37        1         0.5419
      britcolxtime|     -0.03110         0.05        1         0.8169
      ------------+---------------------------------------------------
      global test |                     12.17       12         0.4321
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. *********************************************************
. * 16 - MidGround to Authoritarian - Educational Exchange
. *********************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-aut-stset.dta", clear

. *use "mid-to-aut-stset.dta"
. notes

_dta:
  1.  Data compiled by Carol Atkinson.
  2.  When using cite: Atkinson, Carol. 2006. Constructivist Implications of Material Power: Military Engagement and the Socialization of
      States 1972-2000. International Studies Quarterly. September.

. describe

Contains data from C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-aut-stset.dta
  obs:         1,256                          
 vars:            27                          3 May 2006 21:48
 size:       155,744 (98.5% of memory free)   (_dta has notes)
-------------------------------------------------------------------------------
              storage  display     value
variable name   type   format      label      variable label
-------------------------------------------------------------------------------
ccode           float  %9.0g                  
country         str24  %24s                   
abbrev          str8   %8s                    
year            float  %9.0g                  
polity2         float  %9.0g                  Polity2+10, inconsistencies
                                                removed from conversion of
                                                -66, -77, -88
IMETyesno       float  %9.0g                  IMET indicator,
                                                1=attendance/funding that year,
                                                0=not
Ally            float  %9.0g                  Alliance membership with the
                                                US, 1=yes, 0=no
USMil_normfor~l float  %9.0g                  US Military Overseas normalized
                                                by size of foreign military
USmil_sales_n~m float  %9.0g                  US military sales/GDP-current
USmilasst_norm  float  %9.0g                  US military
                                                assistance/GDP-current
USmilact_yesno  float  %9.0g                  1=threat, display, use of
                                                force, war; 0= no militarized
                                                action by US
soviet_foreig~t float  %9.0g                  Countries receiving foreign
                                                assistance from the USSR during
                                                the Cold War
USeconaid_norm  float  %9.0g                  US economic aid/GDP-current
newc            float  %9.0g                  New country in or after 1945
britcol         float  %9.0g                  Former British colony
open_i          float  %9.0g                  Trade openness indicator
GDP_rescaled    float  %9.0g                  GDP_PPP_per_capita / 1000
Ethnic_gp       float  %9.0g                  Percentage of the population
                                                that is of the country's
                                                largest ethnic group
muslim_majori~o float  %9.0g                  Muslim majority indicator,
                                                Muslims are at least 50%=1, 0
                                                otherwise
christian_maj~o float  %9.0g                  Christian majority indicator,
                                                Christians are at least 50%=1,
                                                0 otherwise
LatAm           float  %9.0g                  1=country in Central or South
                                                America, 0=not
mildictator     float  %9.0g                  Military dictatorship
                                                indicator, 1=military dictator,
                                                0=otherwise
ccode1          float  %9.0g                  
_st             byte   %8.0g                  
_d              byte   %8.0g                  
_t              byte   %10.0g                 
_t0             byte   %10.0g                 
-------------------------------------------------------------------------------
Sorted by:  ccode  year

. #delimit ;
delimiter now ;
. stcox 
> IMETyesno
> USmilact_yesno
> soviet_foreign_asst 
> USeconaid_norm 
> newc 
> britcol
> open_i
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno,
> bases(mgtoaut_surv) basehc(mgtoaut_hazard) basechazard(mgtoaut_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d2 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -124.52679
Iteration 1:   log pseudolikelihood = -115.27025
Iteration 2:   log pseudolikelihood = -114.51495
Iteration 3:   log pseudolikelihood =  -114.5014
Iteration 4:   log pseudolikelihood = -114.50138
Refining estimates:
Iteration 0:   log pseudolikelihood = -114.50138

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           28
Time at risk         =         1180
                                                   Wald chi2(11)   =     21.94
Log pseudolikelihood =   -114.50138                Prob > chi2     =    0.0248

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
   IMETyesno |  -.3612865   .4481008    -0.81   0.420    -1.239548    .5169749
USmilact_y~o |   .1372097   1.575226     0.09   0.931    -2.950177    3.224596
soviet_for~t |   .5075161   .4494984     1.13   0.259    -.3734845    1.388517
USeconaid_~m |  -23.10128   17.49137    -1.32   0.187    -57.38374    11.18118
        newc |  -.0439282   .5727332    -0.08   0.939    -1.166465    1.078608
     britcol |   .7736207   .4030134     1.92   0.055     -.016271    1.563512
      open_i |  -.0069324   .0058038    -1.19   0.232    -.0183077    .0044429
GDP_rescaled |  -.3175835   .1617238    -1.96   0.050    -.6345563   -.0006107
   Ethnic_gp |   1.349876   .7362328     1.83   0.067    -.0931137    2.792866
muslim_maj~o |  -.3579139   .4732148    -0.76   0.449    -1.285398    .5695701
christian_~o |   .6449534     .46484     1.39   0.165    -.2661162    1.556023
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      IMETyesno   |     -0.05647         0.22        1         0.6399
      USmilact_y~o|      0.13421         1.62        1         0.2037
      soviet_for~t|     -0.07134         0.24        1         0.6225
      USeconaid_~m|      0.13275         0.48        1         0.4883
      newc        |     -0.07145         0.30        1         0.5809
      britcol     |      0.03681         0.05        1         0.8257
      open_i      |      0.21397         1.87        1         0.1717
      GDP_rescaled|     -0.16176         1.31        1         0.2517
      Ethnic_gp   |     -0.13981         0.80        1         0.3704
      muslim_maj~o|      0.00353         0.00        1         0.9859
      christian_~o|     -0.11408         0.44        1         0.5052
      ------------+---------------------------------------------------
      global test |                      6.93       11         0.8045
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. *************************************************
. * 17 - MidGround to Authoritarian - Ally With US
. *************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-aut-stset.dta", clear

. *use "mid-to-aut-stset.dta"
. #delimit ;
delimiter now ;
. stcox 
> Ally 
> USmilact_yesno
> soviet_foreign_asst 
> USeconaid_norm 
> newc 
> britcol
> open_i
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno,
> bases(mgtoaut_surv) basehc(mgtoaut_hazard) basechazard(mgtoaut_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d2 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -124.52679
Iteration 1:   log pseudolikelihood = -115.56536
Iteration 2:   log pseudolikelihood = -114.82703
Iteration 3:   log pseudolikelihood = -114.81483
Iteration 4:   log pseudolikelihood = -114.81482
Refining estimates:
Iteration 0:   log pseudolikelihood = -114.81482

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           28
Time at risk         =         1180
                                                   Wald chi2(11)   =     20.99
Log pseudolikelihood =   -114.81482                Prob > chi2     =    0.0335

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
        Ally |   .2427568   .7362827     0.33   0.742    -1.200331    1.685844
USmilact_y~o |   .3332218   1.506385     0.22   0.825    -2.619238    3.285681
soviet_for~t |   .5408917   .4709114     1.15   0.251    -.3820776    1.463861
USeconaid_~m |  -25.93008   19.20447    -1.35   0.177    -63.57015    11.70998
        newc |   .1932279   .6832056     0.28   0.777     -1.14583    1.532286
     britcol |   .7082868   .3881779     1.82   0.068    -.0525279    1.469102
      open_i |  -.0062711   .0058542    -1.07   0.284    -.0177451    .0052029
GDP_rescaled |   -.324176   .1610876    -2.01   0.044    -.6399019   -.0084501
   Ethnic_gp |   1.357003   .7657099     1.77   0.076    -.1437611    2.857766
muslim_maj~o |  -.4048971   .4757652    -0.85   0.395     -1.33738    .5275856
christian_~o |   .5859201   .5119673     1.14   0.252    -.4175173    1.589358
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      Ally        |      0.02941         0.03        1         0.8649
      USmilact_y~o|      0.17441         2.25        1         0.1339
      soviet_for~t|     -0.08142         0.35        1         0.5561
      USeconaid_~m|      0.10348         0.36        1         0.5495
      newc        |     -0.04798         0.11        1         0.7441
      britcol     |     -0.00557         0.00        1         0.9765
      open_i      |      0.18850         1.65        1         0.1985
      GDP_rescaled|     -0.17580         1.28        1         0.2588
      Ethnic_gp   |     -0.16769         1.14        1         0.2855
      muslim_maj~o|      0.04158         0.04        1         0.8332
      christian_~o|     -0.10562         0.48        1         0.4883
      ------------+---------------------------------------------------
      global test |                      6.87       11         0.8096
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. ***************************************************************
. * 18 - MidGround to Authoritarian - US Military Troop Presence
. ***************************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-aut-stset.dta", clear

. *use "mid-to-aut-stset.dta"
. #delimit ;
delimiter now ;
. stcox 
> USMil_normforeignMil 
> USmilact_yesno
> soviet_foreign_asst 
> USeconaid_norm 
> newc 
> britcol
> open_i
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno,
> bases(mgtoaut_surv) basehc(mgtoaut_hazard) basechazard(mgtoaut_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d2 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -124.52679
Iteration 1:   log pseudolikelihood = -117.14075
Iteration 2:   log pseudolikelihood = -113.02896
Iteration 3:   log pseudolikelihood = -112.87291
Iteration 4:   log pseudolikelihood = -112.87105
Iteration 5:   log pseudolikelihood = -112.87105
Refining estimates:
Iteration 0:   log pseudolikelihood = -112.87105

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           28
Time at risk         =         1180
                                                   Wald chi2(11)   =     45.81
Log pseudolikelihood =   -112.87105                Prob > chi2     =    0.0000

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
USMil_norm~l |   1.830084   .4363516     4.19   0.000     .9748506    2.685317
USmilact_y~o |  -.2948846   1.043281    -0.28   0.777    -2.339677    1.749908
soviet_for~t |   .6538806   .4315815     1.52   0.130    -.1920036    1.499765
USeconaid_~m |  -26.98085   19.90775    -1.36   0.175    -65.99932    12.03763
        newc |   .1283254   .5770823     0.22   0.824    -1.002735    1.259386
     britcol |   .6712212   .3860751     1.74   0.082    -.0854721    1.427914
      open_i |  -.0069583   .0065234    -1.07   0.286     -.019744    .0058274
GDP_rescaled |  -.3569989   .1799239    -1.98   0.047    -.7096433   -.0043546
   Ethnic_gp |   1.393917    .774727     1.80   0.072    -.1245205    2.912354
muslim_maj~o |  -.3833291   .4787139    -0.80   0.423    -1.321591    .5549329
christian_~o |   .6313525   .4799552     1.32   0.188    -.3093423    1.572047
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      USMil_norm~l|      0.24206         0.46        1         0.4972
      USmilact_y~o|      0.06083         0.03        1         0.8578
      soviet_for~t|      0.03870         0.05        1         0.8298
      USeconaid_~m|      0.07176         0.18        1         0.6706
      newc        |     -0.10655         0.65        1         0.4211
      britcol     |     -0.02128         0.01        1         0.9085
      open_i      |      0.21717         2.41        1         0.1204
      GDP_rescaled|     -0.24979         3.02        1         0.0821
      Ethnic_gp   |     -0.16576         1.10        1         0.2932
      muslim_maj~o|      0.07105         0.13        1         0.7160
      christian_~o|     -0.10528         0.42        1         0.5162
      ------------+---------------------------------------------------
      global test |                      7.01       11         0.7984
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. ******************************************************
. * 19 - MidGround to Authoritarian - US Military Sales
. ******************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-aut-stset.dta", clear

. *use "mid-to-aut-stset.dta"
. #delimit ;
delimiter now ;
. stcox 
> USmil_sales_norm
> USmilact_yesno
> soviet_foreign_asst 
> USeconaid_norm 
> newc 
> britcol
> open_i
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno,
> bases(mgtoaut_surv) basehc(mgtoaut_hazard) basechazard(mgtoaut_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d2 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -124.52679
Iteration 1:   log pseudolikelihood = -115.45499
Iteration 2:   log pseudolikelihood = -114.67525
Iteration 3:   log pseudolikelihood = -114.66248
Iteration 4:   log pseudolikelihood = -114.66247
Refining estimates:
Iteration 0:   log pseudolikelihood = -114.66247

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           28
Time at risk         =         1180
                                                   Wald chi2(11)   =     25.05
Log pseudolikelihood =   -114.66247                Prob > chi2     =    0.0090

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
USmil_sale~m |  -106.5116   159.4547    -0.67   0.504    -419.0371    206.0139
USmilact_y~o |   .2878792   1.495004     0.19   0.847    -2.642275    3.218034
soviet_for~t |   .5635083   .4649356     1.21   0.226    -.3477487    1.474765
USeconaid_~m |  -23.41103   18.62021    -1.26   0.209    -59.90598    13.08392
        newc |  -.0503813     .60578    -0.08   0.934    -1.237688    1.136926
     britcol |   .7488927   .3858162     1.94   0.052    -.0072932    1.505078
      open_i |  -.0060138    .005919    -1.02   0.310    -.0176148    .0055872
GDP_rescaled |  -.3185639   .1606798    -1.98   0.047    -.6334905   -.0036372
   Ethnic_gp |   1.374979    .744397     1.85   0.065    -.0840118    2.833971
muslim_maj~o |  -.3611249   .4699609    -0.77   0.442    -1.282231    .5599815
christian_~o |   .5939984   .4948373     1.20   0.230    -.3758649    1.563862
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      USmil_sale~m|     -0.14723         0.59        1         0.4442
      USmilact_y~o|      0.15405         1.73        1         0.1886
      soviet_for~t|     -0.03258         0.05        1         0.8166
      USeconaid_~m|      0.13451         0.61        1         0.4354
      newc        |     -0.09935         0.58        1         0.4481
      britcol     |      0.01453         0.01        1         0.9388
      open_i      |      0.22125         2.13        1         0.1447
      GDP_rescaled|     -0.14794         0.90        1         0.3415
      Ethnic_gp   |     -0.15464         0.92        1         0.3372
      muslim_maj~o|      0.05199         0.07        1         0.7950
      christian_~o|     -0.12549         0.64        1         0.4235
      ------------+---------------------------------------------------
      global test |                      6.86       11         0.8104
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. ***********************************************************
. * 20 - MidGround to Authoritarian - US Military Assistance
. ***********************************************************
. version 8.2

. clear

. use "C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\mid-to-aut-stset.dta", clear

. *use "mid-to-aut-stset.dta"
. 
. #delimit ;
delimiter now ;
. stcox 
> USmilasst_norm
> USmilact_yesno
> soviet_foreign_asst 
> USeconaid_norm 
> newc 
> britcol
> open_i
> GDP_rescaled
> Ethnic_gp 
> muslim_majority_yesno 
> christian_majority_yesno,
> bases(mgtoaut_surv) basehc(mgtoaut_hazard) basechazard(mgtoaut_cumhaz) nohr efron schoenfeld(sch*) scaledsch(sca*) cluster(ccode);

         failure _d:  d2 == 1
   analysis time _t:  timem1
                 id:  ccode1

Iteration 0:   log pseudolikelihood = -124.52679
Iteration 1:   log pseudolikelihood = -115.58359
Iteration 2:   log pseudolikelihood = -114.82606
Iteration 3:   log pseudolikelihood = -114.81393
Iteration 4:   log pseudolikelihood = -114.81391
Iteration 5:   log pseudolikelihood = -114.81391
Refining estimates:
Iteration 0:   log pseudolikelihood = -114.81391

Cox regression -- Efron method for ties

No. of subjects      =          135                Number of obs   =      1180
No. of failures      =           28
Time at risk         =         1180
                                                   Wald chi2(11)   =     21.61
Log pseudolikelihood =   -114.81391                Prob > chi2     =    0.0276

                                (Std. Err. adjusted for 105 clusters in ccode)
------------------------------------------------------------------------------
             |               Robust
          _t |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
USmilasst_~m |  -21.30109   46.58107    -0.46   0.647    -112.5983    69.99612
USmilact_y~o |    .317309   1.504986     0.21   0.833    -2.632409    3.267027
soviet_for~t |   .5609811   .4735537     1.18   0.236     -.367167    1.489129
USeconaid_~m |  -24.41885   19.34692    -1.26   0.207    -62.33812    13.50041
        newc |  -.0017034   .5715231    -0.00   0.998    -1.121868    1.118461
     britcol |   .7232485   .3902079     1.85   0.064     -.041545    1.488042
      open_i |  -.0061894   .0059388    -1.04   0.297    -.0178293    .0054505
GDP_rescaled |  -.3282033   .1609303    -2.04   0.041     -.643621   -.0127857
   Ethnic_gp |   1.390057   .7478223     1.86   0.063    -.0756474    2.855762
muslim_maj~o |  -.3792098   .4771009    -0.79   0.427     -1.31431    .5558907
christian_~o |    .633564    .466962     1.36   0.175    -.2816646    1.548793
------------------------------------------------------------------------------

. stphtest, detail;

      Test of proportional hazards assumption

      Time:  Time
      ----------------------------------------------------------------
                  |       rho            chi2       df       Prob>chi2
      ------------+---------------------------------------------------
      USmilasst_~m|     -0.12730         0.25        1         0.6202
      USmilact_y~o|      0.15999         1.89        1         0.1691
      soviet_for~t|     -0.03702         0.07        1         0.7870
      USeconaid_~m|      0.12965         0.57        1         0.4504
      newc        |     -0.07723         0.34        1         0.5621
      britcol     |      0.01187         0.00        1         0.9504
      open_i      |      0.20982         1.94        1         0.1636
      GDP_rescaled|     -0.16244         1.10        1         0.2953
      Ethnic_gp   |     -0.15722         0.94        1         0.3328
      muslim_maj~o|      0.04622         0.05        1         0.8153
      christian_~o|     -0.09963         0.35        1         0.5520
      ------------+---------------------------------------------------
      global test |                      6.64       11         0.8273
      ----------------------------------------------------------------

note: robust variance-covariance matrix used.

. #delimit cr
delimiter now cr
. clear

. 
. log close
       log:  C:\a CAROL ISQ  article - 2006\DATA FOR POSTING - ISQ\table1b.log
  log type:  text
 closed on:   3 May 2006, 22:51:12
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